Estimating IBD tracts from low coverage NGS data

TY - JOUR

T1 - Estimating IBD tracts from low coverage NGS data

AU - Garrett Vieira, Filipe Jorge

AU - Albrechtsen, Anders

AU - Nielsen, Rasmus

N1 - © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected].

PY - 2016/7/15

Y1 - 2016/7/15

N2 - Motivation: The amount of IBD in an individual depends on the relatedness of the individual's parents. However, it can also provide information regarding mating system, past history and effective size of the population from which the individual has been sampled. Results: Here, we present a new method for estimating inbreeding IBD tracts from low coverage NGS data. Contrary to other methods that use genotype data, the one presented here uses genotype likelihoods to take the uncertainty of the data into account. We benchmark it under a wide range of biologically relevant conditions and show that the new method provides a marked increase in accuracy even at low coverage. Availability and implementation: The methods presented in this work were implemented in C/C ++ and are freely available for non-commercial use from https://github.com/fgvieira/ngsF-HMM. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

AB - Motivation: The amount of IBD in an individual depends on the relatedness of the individual's parents. However, it can also provide information regarding mating system, past history and effective size of the population from which the individual has been sampled. Results: Here, we present a new method for estimating inbreeding IBD tracts from low coverage NGS data. Contrary to other methods that use genotype data, the one presented here uses genotype likelihoods to take the uncertainty of the data into account. We benchmark it under a wide range of biologically relevant conditions and show that the new method provides a marked increase in accuracy even at low coverage. Availability and implementation: The methods presented in this work were implemented in C/C ++ and are freely available for non-commercial use from https://github.com/fgvieira/ngsF-HMM. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

KW - Journal Article

U2 - 10.1093/bioinformatics/btw212

DO - 10.1093/bioinformatics/btw212

M3 - Journal article

C2 - 27153648

SN - 1367-4803

VL - 32

SP - 2096

EP - 2102

JO - Bioinformatics

JF - Bioinformatics

IS - 14

ER -